class_docstr: Base class to apply hidden state transformations
class_docstr_tok: ["Base","class","to","apply","hidden","state","transformations"]
docstr: Implement your own transformations.
  We expect here shapes to be [S x B x H] for Sequence, Batch, Hidden sizes (due to tensor parallel support).
docstr_tok: ["Implement","your","own","transformations",".","We","expect","here","shapes","to","be","[","S","x","B","x","H","]","for","Sequence",",","Batch",",","Hidden","sizes","(","due","to","tensor","parallel","support",")","."]
code: def _transform(self, inputs, batch_data=None):
      """
      Implement your own transformations.
      We expect here shapes to be [S x B x H] for Sequence, Batch, Hidden sizes (due to tensor parallel support).
      """
      # by default we pass inputs.
      outputs = inputs.copy()
  
      return outputs
  
file_path: NeMo/nemo/collections/nlp/modules/common/megatron/hiddens/megatron_hidden_transform.py
imports: import math
  import torch
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, init_method_normal
label_desc: Use image node_id 6 for calling the MegatronBaseHiddenTransform obj's underlying member method code with example usage: obj._transform(inputs, batch_data) and returns: outputs